Every so often, an old story finds a new lease of life on a news website thanks to social media and the ‘most read’ stories panel. In the wake of the Paris terror attack, for example, social sharing caused a story about an attack in Kenya to begin trending — many of those sharing it didn’t realise that it had happened seven months earlier.

The problem is a symptom of the permanence of digital information. Old newspaper stories and broadcast bulletins never had to deal with this problem — but those organisations do now.

The broader problem was that many users, experiencing the video for the first time, and coming from other publishing contexts online (different headlines on social media) may not know the wider context surrounding it. As the Guardian report:

“The BBC website, under the headline “Jeremy Corbyn opposes ‘shoot to kill’ policy”, makes no mention that the interview was subject to an upheld complaint over accuracy. Nor does the BBC make it clear that the video dates from 2015, or is a 33-second extract taken from a longer interview. The only date credit visible on the page hosting the video is the ambiguous “16 Nov”.

This is not, however, a post about this specific handling of one contentious video. Rather it highlights once again the broader issue of archive stories which suddenly find a new lease of life.

Old news is changed by new news, and vice versa

Old news often becomes news again, but only because of new context. What a politician said two years ago, or an attack that happened six months ago, might become newsworthy because it sheds new light on current events.

But equally those current events shed a new light on old news. The question is, how do we make that new context clear to online audiences?

Reports in the Sunand Daily Mail on the Corbyn video “going viral” place the old video in new context. Casual browsers of the site don’t see stories claiming that “Jeremy Corbyn opposes ‘shoot to kill’ policy” but rather headlines about a “U-turn” from that policy.

4 things we can do with old news

How do we ensure that people stumbling across the video from November 2015 know what is happening on that front in June 2017? How do we ensure, in other words, that they know what is new?

There’s not a simple answer: archives are important records of what happened at the time, and it’s important to see how things were reported. We shouldn’t attempt to rewrite history.

But providing context is what news organisations do. At the most basic level date stamps should certainly have more prominence than they do — not having a year on an article timestamp is an incredible oversight for a news organisation’s content management system — but dates should also be perhaps made more prominent when the article is past a certain date, so that the reader is made aware that what they are reading is not happening now.

April Fool’s Day entries deserve a special category all of their own.

And when an old story begins receiving higher than normal attention? Well that should certainly trigger some editorial attention. Aside from anything else, surely we want readers stumbling across this old piece of content to then continue to other content on our site such as any recent developments around the same issue: a ‘what’s happening on this story now’ box seems a no-brainer not just in terms of accuracy, but commercial opportunity. (The old Corbyn interview features two – presumably automated – links to ‘Jeremy Corbyn’ videos but neither is the latest video interview where Corbyn reaffirms his position, and there are no links to non-video stories).

More broadly, we might also want to consider meta data which is used to populate Twitter cards and other social media previews, to clarify the date of the content in question. If a Twitter card says “Earthquake in Italy” and that happened last year, the date should be part of the headline: it’s history, not news.

Along the same lines, when the headline makes the most-read boxes we need to consider how to avoid users who scan-read that headline assuming that it refers to current events.

Ultimately an algorithm is only as good as its designers, and will inevitably need monitoring and adjusting as problems surface and people try to ‘game’ the algorithm.

The ‘most read stories’ algorithms are based on a flawed premise: that people only, always, share the most recent or timeless stories. But as our digital history gets longer, and the gaming of news algorithms gets more clever, we need to make sure our systems aren’t misleading our audiences.